
We propose to deploy RIS on the aerial platform to establish backhaul links with rich-LoS component to the UAV-BSs [1]}, which leverages the advantages of both a high-altitude platform and the RIS. We first adapt the maximum-ratio transmission (MRT) strategy to maximize the received signal-to-noise ratio (SNR) and hence lower the transmit power.

To achieve a high energy-efficiency, we derive a non-zero lower-bound on the source transmit power for every UAV-BS and minimize the bounds by minimizing and maximizing their numerator and denominator, respectively. For the numerator, we minimize the multiplications of squared-distance for each UAV-BS by solving the cubic equation and achieving the Pareto-optimum among the location candidates using the method of global criterion. For the denominator, we maximize the objective function by determining the phase aligning strategy, consisting of the array-partition-mode selection and the exploitation of the relationship between the passive beamforming gain and the sin-angle-deviations. In case that the array-partition is necessary, we propose to apply our “reverse-waterfilling” array-partitioning strategy that minimizes the sum of the lower bound of transmit power and determine the optimal number of array-partition by a one-dimensional search.

Through our novel framework of aerial-RIS deployments, we optimize the placement, array-partition, and phase alignment of aerial-RIS to minimize the source transmit power under the fronthaul-rate-ensuring constraints. Furthermore, we show that the computational complexity of the proposed algorithm is upper-bounded by the quadratic order, which shows a high computational efficiency. We numerically estimate the performance of the proposed algorithm in a realistic urban outdoor scenario with randomly distributed ground users and corresponding UAV-BSs. By extensive simulations, we demonstrate substantial improvements of energy-efficiency by the proposed algorithm.

